Project Background – SILC & the PSP model
Savings and Internal Lending Communities (SILC) is a model developed by Catholic
Relief Services for user-owned, self-managed, savings and credit groups. A SILC
typically comprises 15-30 self-selecting members, and oﬀers a frequent, convenient
and safe opportunity to save. SILC helps members build useful lump sums that
become available at a pre-determined time and allows them to access small loans or
emergency grants for investment and consumption.
SILC Innovations is a pilot project within CRS’ broader SILC program, funded by
the Bill & Melinda Gates Foundation from 2008-2012, which aims to establish local
entrepreneurial capacity for sustaining the spread of the savings-group model
beyond the funding period. In the project design, the Field Agents (FA) responsible
for forming and supporting SILC groups are recruited and paid by the project for
up to one year. The FAs then undergo an examination process to become certified
as Private Service Providers (PSP), who oﬀer their SILC services to communities
on a long-term, fee-for-service basis, with no further project funding. The project
currently serves over 350,000 savings group members, mostly rural villagers, across
the three pilot countries of Kenya, Tanzania, and Uganda.

KEY FINDINGS ON GROUP PERFORMANCE:
• PSP-supported groups are outperforming FA-supported groups on key financial measures,
such as individual savings levels, group assets, and loan sizes.
• On membership measures, PSP-supported groups are outperforming FA-supported groups
on member growth rates and showing comparable results on drop-out rates and gender
composition.
• Baseline-endline comparisons of the portfolios of randomized agents confirmed that these trends
emerged post-randomization, thereby confirming the attribution to the PSP model.

Research Design and Group Performance
To assess the model and inform future SILC rollouts on this fee-for-service, savingsgroup delivery channel, CRS carried out a broad research study using a Randomized
Control Trial (RCT) design. The research was set up to make a fundamental
comparison between two delivery channels: the fee-for-service PSP model and
the more conventional project-paid FA model. To rigorously compare the two, an
experimental design established statistically comparable cohorts of agents serving
members in comparable environments over approximately a one-year interval (see the
additional research background section on page 8).

On membership,
we see that PSPs
were supporting
signiﬁcantly larger
groups on average
(consistent with
ﬁndings elsewhere in
this RCT).

In total, the study tracked 333 randomized agents across two cohorts (separated by
about one year). The agents were assigned either fee-for-service PSP status or stipendpaid FA status for the research interval, which followed a 12-month training phase
in which all agents were paid a stipend. Management Information System data was
collected from all agents on a quarterly basis and included a multitude of data points.
This brief draws on the data specifically pertaining to group performance, focusing
on the comparison between groups served by randomized PSPs and groups served
by randomized FAs. A central question was at the core: can we detect systematic
diﬀerences in group performance between PSP-supported and FA-supported groups?

Randomized Comparisons on Group Performance
To make these comparisons, we employed the data set for groups created and served
in the RCT period by the randomized agents (n = 1,996 groups).1 The data that went
into the set was drawn from the quarterly observation following the end of the one-year
randomization period in each region of the study.2 The metrics tracked and reported
here can be divided into two group-performance categories: membership and finances.
On membership, we see that PSPs were supporting significantly3 larger groups on
average (consistent with findings elsewhere in this RCT). PSPs also led on membership
growth within cycle, with the country breakdown indicating that the results are being
driven clearly by the Kenyan subpopulation. On dropout rates and percentages of
female members, we see mostly parity across the two delivery channels, though in
certain subpopulations the FA-supported groups hold a moderately significant edge.

1 In terms of cycles, the group sample breaks down as follows: 89 percent first cycle, 11 percent second cycle, less than 1
percent third+ cycle.
2 It is important to note that what we have in this data is a “snapshot” of group performance, taken immediately at the
end of each agent’s randomization period. The data is not representative of complete group cycles, as those cycles do not
correspond neatly with the randomization period. For example, average savings balances are not the full average value
of savings built by members over a cycle, but rather the average amount saved when the randomization period ended in
each region. The critical point here is comparability—the “snapshots” need to be comparable between the PSP-supported
groups and the FA-supported groups, which they are.
3 Significance measures are two-tailed, generated by t-tests, with thresholds as indicated in table key. Corresponding assumptions on variance made using results of Levene’s Test (p < 0.05). Three stars indicate the most significant diﬀerences,
followed by two, and one, per the p-values in the text box next to the table. Zero stars indicate that there was no significant diﬀerence.

2

TABLE 1 - MEMBERSHIP-RELATED GROUP PERFORMANCE COMPARISONS 45

Overall
Kenya
Tanzania
Uganda
Cohort 1
Cohort 2

* P<.10

PSP groups are
offering their
members signiﬁcantly
larger loans on
average, and offering
more sizeable returns.

Rand
Status

Number of
Groups5

Avg.
Group Size

FA

830

20.6**

PSP

1166

FA

Avg. Growth in
Membership (within cycle)

Dropout Rate
(within cycle)

Avg. Percentage
of Women

24.2%**

0.1%

72.3%

21.2

29.4%

0.2%

73.5%

335

19.0**

29.9%**

0.2%

81.0%

PSP

617

19.8

38.3%

0.2%

83.0%

FA

327

20.2***

23.1%

0.1%

65.8%**

PSP

452

22.0

20.3%

0.2%

62.7%

FA

168

24.3***

14.9%

0.0%

67.4%*

PSP

97

26.5

15.6%

0.0%

63.1%

FA

254

18.9***

23.9%**

0.2%

71.2%

PSP

221

21.1

36.9%

0.0%

71.4%

FA

576

21.3

24.3%

0.1%**

72.7%

PSP

945

21.2

27.7%

0.2%

74.0%

** P<0.05

*** P<0.01 Red = PSPs lead Blue = FAs lead

The overall trend emerges much more clearly when we begin to look at group
financial metrics (Table 2). Beginning with the overall results, PSP groups are
significantly outperforming FA groups on core functions, such as members’ savings
(both individual balances and per-week contributions), member assets, and group
assets. PSP groups are oﬀering their members significantly larger loans on average6,
and oﬀering more sizeable returns, as measured via the Return on Savings (ROS)
and Annualized Return on Assets (AROA) metrics7 (Table 3). We note here that
other aspects of this research have proven that the individuals in PSP groups are not
wealthier than the individuals in FA groups, on average—consequently higher savings
levels are not the result of greater member wealth.8
Those same diﬀerences clearly emerge in the country-specific findings. Uganda
oﬀers the only cases where FA groups show significantly higher results than PSP
groups on percent of assets loaned out and percent of members with loans, which
in turn has had a significant negative eﬀect on the former measure overall. At this
time, we cannot oﬀer any concrete explanation for this divergence, but we note: 1)
Uganda is by far the smallest country-specific sample (365 of 1,996 total groups); and
2) the results are not enough to alter the significance of key measures in the overall
sample, which includes Uganda.

4 All figures here and elsewhere in this brief are group-level calculations, averaged across the data set.
5 The asymmetrical sample was a deliberate decision to account for the anticipated higher variance in the results from PSP agents.
6 A finding confirmed by the Savix team at www.savingsgroups.com.
7 One qualification to the ROS and AROA comparisons is that these return rates do not take into account the fees paid to
the agents—hence a net return in the case of PSP groups would be somewhat lower. However, we have every reason to
believe that these high rates of return would remain at these levels as the PSP groups progress into later cycles, where
they typically see their payments to the agents reduce or discontinue.
8 For additional details, see “SILC Innovations Research Brief 1: Poverty Outreach in Fee-for-Service Savings Groups.”

3

TABLE 2 - FINANCE-RELATED GROUP PERFORMANCE COMPARISONS, PART I

Rand
Status

Overall
Kenya
Tanzania
Uganda
Cohort 1
Cohort 2
* P<.10

No. of
Groups

Avg.
Group
Assets

Avg.
Percent
of Assets
Loaned
Out

Avg.
Member
Savings
Balance

Avg.
Member
Savings
per Week

Avg.
Member
Assets

Avg. % of
Members
with Loans
Outstanding

Avg. Loan
Value
Outstanding

FA

830

$434***

83.3%**

$16***

$0.97***

$21***

60.1%***

$28***

P

1166

$662

80.9%

$23

$1.19

$30

64.4%

$36

FA

335

$418***

75.8%

$15***

$0.90***

$21***

58.1%***

$27***

PSP

617

$684

77.7%

$24

$1.22

$33

70.8%

$34

FA

327

$425***

91.7%

$16***

$1.18

$21***

62.8%

$31***

PSP

452

$631

90.8%

$22

$1.23

$28

62.3%

$40

FA

168

$484**

81.9%***

$14**

$0.67

$19**

58.7%***

$24**

PSP

97

$673

54.8%

$18

$0.80

$24

33.0%

$32

FA

254

$396**

81.2%

$15*

$0.90

$21

57.2%

$31

PSP

221

$531

79.8%

$18

$0.94

$25

57.1%

$32

FA

576

$451***

84.2%**

$1.00***

$20***

61.4%***

$27***

PSP

945

$693

81.2%

$1.24

$32

66.1%

$37

$16***
$24

** P<0.05 *** P<0.01 Red = PSPs lead Blue = FAs lead

TABLE 3 - FINANCE-RELATED GROUP PERFORMANCE COMPARISONS, PART II

Rand Status
Overall

Kenya

Tanzania

Uganda

Cohort 1

Cohort 2

* P<.10

Return on Savings

Annualized Return on Assets

FA

20.0%***

27.9%***

PSP

23.1%

34.2%

FA

21.7%***

33.0%***

PSP

26.7%

39.4%

FA

18.4%

32.6%

PSP

17.9%

30.7%

FA

19.9%*

14.2%**

PSP

24.1%

19.4%

FA

22.4%

32.2%

PSP

21.4%

30.6%

FA

19.0%***

26.0%***

PSP

23.5%

35.0%

** P<0.05 *** P<0.01 Red = PSPs lead Blue = FAs lead

As in other areas of our RCT analysis, we disaggregated by cohort to determine
whether project learning from the first cohort led to better agent selection or process
improvement, thereby improving group performance between the first and second
cohorts. Generally, the results confirmed this trend of improvement. Though Cohort 1
already shows some significant advantages for the PSP-supported groups, the gaps
widen in Cohort 2 as the PSP groups pull away significantly from the FA groups on
core financial measures, such as group assets, individual savings levels, loan size, and
ROS/AROA.
4

As such, the PSP-supported groups have outpaced FA-supported groups on the
performance measures deemed most important to this project. The PSP groups are
growing faster, saving more (both at the group and individual level), and oﬀering
higher returns to members. Thus PSP supported SILC members have access to larger
lump sums in the form of loans and share-outs than FA supported ones.

Baseline-endline Comparison on Group Performance
To gain a more contoured understanding of the diﬀerences noted in Tables 2 and
3, we calculated baseline measures of group performance for the portfolios of the
randomized agents—in other words, using only the groups created while the agents
remained undiﬀerentiated in the pre-randomization, 12-month agent training phase,
as their original portfolio in the table. As such, the agents in this undiﬀerentiated first
line are still shown as FA/PSP because these are the statuses that the agents went on to
assume in the randomization. In this way, we can compare to the endline results above
to isolate the change-over-time impact and ensure that the diﬀerences in Tables 2 and
3 were not produced by a faulty randomization.

Generally, the results confirm the validity of the above impacts. On the baseline
financial measures, we see limited diﬀerentiation between PSP and FA groups, and
in fact, FA groups hold a slight lead in several categories, including group assets,
individual savings balance, ROS, and AROA (Tables 4 and 5, Line 1). This trend
completely vanishes in the endline measures for the groups created under randomized
status, where the PSP-supported groups have pulled away on all core financial
measures, such as group assets, individual savings, loan size, and ROS/AROA (Tables
4 and 5, Lines 2).
TABLE 4 - BASELINE-ENDLINE COMPARISONS OF GROUP PERFORMANCE MEASURES, PART I

In Figure 1, we graphically demonstrate this divergence between groups created
pre-randomization and post-randomization on key financial metrics (Figure 1). The
diﬀerences are statistically significant (i.e., insignificant diﬀerences at baseline becoming
significant diﬀerences at endline) and indicate a clear positive trend for the PSP
supported groups over time—which we can attribute to the diﬀerent delivery channels.
Moreover, this significance occurred in the relatively short interval of one year.
FIGURE 1  PRE- AND POST-RANDOMIZATION TRENDS FOR INDIVIDUAL SAVING BEHAVIOR

Average Member Savings Balance
$25

Average Member Savings per Week

$20

$1.20

$15

$1.00
$0.80

$10

$0.60

$5

$0.40

$0

FA

PSP

Pre-Randomization

FA

PSP

Post-Randomization

$0.20
$0.00

FA

PSP

Pre-Randomization

PSP

Post-Randomization

Average Loan Value Outstanding

Average Member Equity
$30

$40
$35

$25

$30

$20

$25

$15

$20
$15

$10

$10

$5
$0

FA

$5
FA

PSP

Pre-Randomization

FA

PSP

Post-Randomization

$0

FA

PSP

Pre-Randomization

FA

PSP

Post-Randomization

6

As a final point, we look at the endline performance of groups carried over from the
12-month training period (Tables 4 and 5, Line 3) and compare them to the baseline,
which examined those same groups at the start of the randomization period. In other
words, we have seen how group performance improved among groups created after
agents assumed PSP status, but does that same trend apply to the agents’ original prerandomization portfolio, which agents created as FAs (in training) but continued to
serve as PSPs?
For the most part, the endline measures for this original portfolio show advantageous
changes for the PSP-supported groups. The slightly significant edge that FA-supported
groups held at baseline in terms of groups’ assets and individual savings’ balances has
disappeared. Moreover, member savings per week has pulled away in favor of the
PSP-supported groups for a 17 percent gap at endline. We consider this one of our most
important group metrics as it is a promising indication that at least some of the PSPs’
superior service was applied retroactively to groups created in the FA training phase.

Conclusion: PSPs Stand Out

Member savings per
week has pulled away
in favor of the PSPsupported groups
for a 17 percent gap
at endline.

In a research study that pits fee-for-service agents against agents oﬀering their services
for free, an underlying hypothesis was that the market forces surrounding the PSP
work would compel PSPs to distinguish themselves. That is to say, the PSPs would be
driven to provide superior service to FAs, in order to create suﬃcient demand and earn
a living from their groups. That superior service would manifest in elevated group
performance, among other dimensions.
We have strong evidence to support this hypothesis on the group performance
measures deemed most important to this project. PSP-created groups are growing
more rapidly, saving more, building more assets, and oﬀering larger loans and returns
to their members, despite the fact that the SILC members are just as poor as those in
the FA-supported groups. We see this trend clearly in the interval of one year and fully
expect it will continue over a longer period. To the extent that ongoing agent support
helps maintain strong group performance over time, PSP longevity should lead to
sustained group performance beyond the project timeframe.

7

Additional Research Background
a. Design of the RCT
The study’s experimental design was intended to create statistically comparable cohorts
of agents, serving villages and households in comparable environments. Among FAs
who successfully completed their examination and qualified to be certified as PSPs,
some were randomly assigned for immediate certification (treatment), while others
were randomly assigned to remain as FAs for an additional 12 months (control), before
oﬃcially becoming PSPs. The treatment and control agents were equally qualified, and
were supervised and supported in the same way. The only diﬀerence was how they were
paid – by the project (control) or by the SILC groups (treatment).
The design thereby controls for observable and unobservable diﬀerences between agents,
their supervisors and areas of operation. Through randomization, the treatment PSPs
and the control FAs are statistically comparable and any diﬀerences in performance and
outcomes can be attributed to the delivery channel.
A total of 333 agents were selected for the study. The household survey focused on a
subset of 240 such agents and the villages they served.
b. Research questions/issues
The RCT compares PSP and the FA delivery channels along the following dimensions:
• Group quality and financial performance
• Impact on group members and their households
• Poverty outreach
• Member satisfaction with agent services
• Agent satisfaction with their work and remuneration
• Competitiveness with respect to other financial service providers
• Sustainability of services to groups
c. Data Sources
CRS is employing four primary data sources in the research:
1. The project’s existing Management Information System, which tracks agent
productivity and group financial performance (quarterly).
2. Agent self-reports on their work and income (every six months).
3. Qualitative research with agents and with group members, carried out by
MicroSave, regarding satisfaction with the delivery channel and other topics
(baseline/endline).

4. A household survey, designed in collaboration with Professor Joe Kaboski of Notre
Dame University and administered by Synovate, of both SILC members and nonmembers in 240 villages to establish impact (baseline/endline).

Group Performance in Fee-for-Service Savings Groups

This research paper shares findings from a large-scale Randomized Control Trial of households that participated in Savings and Internal Lending Community groups in Kenya, Tanzania and Uganda. The data compares the performance of groups supported by Private Service Providers and groups supported by project-paid field agents.